Distributed coverage optimization for small cell clusters using game theory

Liang Huang, Yiqing Zhou, Xue Han, Yuanyuan Wang, Manli Qian, Jinglin Shi

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

15 Citations (Scopus)

Abstract

Small cell cluster is a new paradigm to extend the usage of small cells from residential environment to large indoor or outdoor areas. However, coverage optimization is a challenge due to the ad-hoc deployment and plug-and-play feature of small cells. This paper considers decentralized self-optimization network (SON) architecture of small cell cluster and proposes distributed coverage optimization algorithm using game theory (DGT). A non-cooperate game is modeled to tune the Tx power of each small cell with a net utility function considering both gain of throughput and punishment of interference. Nash Equilibrium (NE) is proved to be existed in the game and a power update scheme is proposed which converges to the NE. Simulation results show that DGT can significantly improve throughput as well as coverage ratio with only several iterations. Compared with centralized algorithm such as modified particle swarm optimization (MPSO) and simulated annealing (SA), DGT algorithm reaches higher network throughput, uses less iteration and keeps considerable coverage ratio.

Original languageEnglish
Title of host publication2013 IEEE Wireless Communications and Networking Conference, WCNC 2013
Pages2289-2293
Number of pages5
DOIs
Publication statusPublished - 2013
Event2013 IEEE Wireless Communications and Networking Conference, WCNC 2013 - Shanghai, China
Duration: 7 Apr 201310 Apr 2013

Other

Other2013 IEEE Wireless Communications and Networking Conference, WCNC 2013
CountryChina
CityShanghai
Period7/04/1310/04/13

Keywords

  • Coverage Optimization
  • Coverage Ratio
  • Game Theory
  • Small Cell
  • Small Cell Cluster
  • Throughput

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